A MAP-based SAGE channel estimation and data detection joint algorithm for MIMO system

In recent years, MIMO (Multiple-Input Multiple-Output) have attracted much attention in the study of the next generation wireless communication systems. In this paper, we propose a new channel estimation and data detection joint algorithm for MIMO system using MAP-based SAGE (Space-Alternating Generalized Expectation-maximization) algorithm. In the MAP-based SAGE algorithm we divide a sub-frame of MIMO system into some sub-blocks and use the MAP-based SAGE algorithm in each sub-block. At the head of each sub-frame, we insert a training symbol which is used to initial estimation at the beginning. In the iteration process, we apply channel estimation of the previous sub-block to initial estimation in the current sub-block by ML detection. In the current sub-block we update channel estimate and data detection by iteration until converge. In each iteration process, only part of the transmit antennas is updated. Simulation results show that the proposed algorithm can improve BER performance.